一种基于变分贝叶斯理论的椭圆形扩展目标跟踪方法

兰州理工大学学报 ›› 2025, Vol. 51 ›› Issue (3): 81-88.

• 自动化技术与计算机技术 • 上一篇下一篇

一种基于变分贝叶斯理论的椭圆形扩展目标跟踪方法

陈辉^*1, 王莉¹, 张天佑², 张光华³

1.兰州理工大学电气工程与信息工程学院, 甘肃兰州 730050;
2.甘肃省科学院自动化研究所, 甘肃兰州 730050;
3.西安交通大学电子与信息工程学院, 陕西西安 710049

收稿日期:2022-08-08 出版日期:2025-06-28 发布日期:2025-06-30
通讯作者: 陈辉(1978-),男,山西闻喜人,博士,教授,博导.Email:huich78@hotmail.com
基金资助:
国家自然科学基金(62163023,61873116,62173266,62103318),甘肃省教育厅产业支撑计划(2021CYZC-02)

An elliptical extended target tracking method based on variational Bayesian filtering under abnormal noise conditions

CHEN Hui¹, WANG Li¹, ZHANG Tian-you², ZHANG Guang-hua³

1. College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China;
2. Institute of Automation, Gansu Academy of Sciences, Lanzhou 730050, China;
3. Faculty of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China

Received:2022-08-08 Online:2025-06-28 Published:2025-06-30

摘要/Abstract

摘要： 针对厚尾噪声条件下椭圆扩展目标跟踪问题,基于变分贝叶斯推断提出了一种鲁棒性学生t椭圆形扩展目标跟踪方法.首先,采用学生t分布对非高斯厚尾过程和量测噪声进行建模,利用K-L散度寻找最接近学生t分布的高斯分布,并将后验概率密度近似为高斯分布.其次,用服从逆威沙特分布的随机正定矩阵来描述椭圆形状大小和方向,然后基于分层高斯状态空间模型和变分贝叶斯方法推导出未知尺度矩阵和辅助随机变量,联合递推出目标的运动状态和形状扩展状态.最后,通过构建相应的仿真实验验证了所提算法的有效性和鲁棒性.

关键词: 扩展目标跟踪, 厚尾噪声, 变分贝叶斯滤波, 随机矩阵

Abstract: Aiming at the problem of ellipse extended target tracking under thick-tailed noise, a robust Student’s t extended target method is proposed based on variational Bayesian inference. Firstly, the Student’s t distribution is used to model the non-Gaussian thick-tailed process and measurement noise. The K-L divergence is adopted to find the Gaussian distribution closest to the Student’s t distribution, allowing the posterior probability densityto be approximated as a Gaussian distribution. Secondly, a random positive definite matrix following an inverse Wishart distribution is applied to describe the size and direction of the ellipse shape. Based on the hierarchical Gaussian state space model and variational Bayesian method, the unknown scale matrix and auxiliary random variables are derived to jointly derive the motion state and shape expansion state of the target recursively. Finally, simulation experimental results verify the proposed algorithm efficiency and robustness.

Key words: extended target tracking, thick-tailed noise, variational Bayesian filtering, random matrix

中图分类号:

TP273

陈辉, 王莉, 张天佑, 张光华. 一种基于变分贝叶斯理论的椭圆形扩展目标跟踪方法[J]. 兰州理工大学学报, 2025, 51(3): 81-88.

CHEN Hui, WANG Li, ZHANG Tian-you, ZHANG Guang-hua. An elliptical extended target tracking method based on variational Bayesian filtering under abnormal noise conditions[J]. Journal of Lanzhou University of Technology, 2025, 51(3): 81-88.

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一种基于变分贝叶斯理论的椭圆形扩展目标跟踪方法

An elliptical extended target tracking method based on variational Bayesian filtering under abnormal noise conditions

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